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Mercurial Automation
This directory contains code and utilities for building and testing Mercurial on remote machines.
The automation.py Script
automation.py is an executable Python script (requires Python 3.5+) that serves as a driver to common automation tasks.
When executed, the script will bootstrap a virtualenv in <source-root>/build/venv-automation then re-execute itself using that virtualenv. So there is no need for the caller to have a virtualenv explicitly activated. This virtualenv will be populated with various dependencies (as defined by the requirements.txt file).
To see what you can do with this script, simply run it:
$ ./automation.py
Local State
By default, local state required to interact with remote servers is stored in the ~/.hgautomation directory.
We attempt to limit persistent state to this directory. Even when performing tasks that may have side-effects, we try to limit those side-effects so they don't impact the local system. e.g. when we SSH into a remote machine, we create a temporary directory for the SSH config so the user's known hosts file isn't updated.
AWS Integration
Various automation tasks integrate with AWS to provide access to resources such as EC2 instances for generic compute.
This obviously requires an AWS account and credentials to work.
We use the boto3 library for interacting with AWS APIs. We do not employ any special functionality for telling boto3 where to find AWS credentials. See https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html for how boto3 works. Once you have configured your environment such that boto3 can find credentials, interaction with AWS should just work.
Hint
Typically you have a ~/.aws/credentials file containing AWS credentials. If you manage multiple credentials, you can override which profile to use at run-time by setting the AWS_PROFILE environment variable.
Resource Management
Depending on the task being performed, various AWS services will be accessed. This of course requires AWS credentials with permissions to access these services.
The following AWS services can be accessed by automation tasks:
- EC2
- IAM
- Simple Systems Manager (SSM)
Various resources will also be created as part of performing various tasks. This also requires various permissions.
The following AWS resources can be created by automation tasks:
- EC2 key pairs
- EC2 security groups
- EC2 instances
- IAM roles and instance profiles
- SSM command invocations
When possible, we prefix resource names with hg- so they can easily be identified as belonging to Mercurial.
Important
We currently assume that AWS accounts utilized by us are single tenancy. Attempts to have discrete users of automation.py (including sharing credentials across machines) using the same AWS account can result in them interfering with each other and things breaking.
Cost of Operation
automation.py tries to be frugal with regards to utilization of remote resources. Persistent remote resources are minimized in order to keep costs in check. For example, EC2 instances are often ephemeral and only live as long as the operation being performed.
Under normal operation, recurring costs are limited to:
- Storage costs for AMI / EBS snapshots. This should be just a few pennies per month.
When running EC2 instances, you'll be billed accordingly. By default, we use small instances, like t3.medium. This instance type costs ~$0.07 per hour.
Note
When running Windows EC2 instances, AWS bills at the full hourly cost, even if the instance doesn't run for a full hour (per-second billing doesn't apply to Windows AMIs).
Managing Remote Resources
Occassionally, there may be an error purging a temporary resource. Or you may wish to forcefully purge remote state. Commands can be invoked to manually purge remote resources.
To terminate all EC2 instances that we manage:
$ automation.py terminate-ec2-instances
To purge all EC2 resources that we manage:
$ automation.py purge-ec2-resources